PART 1

Question 1:

image.png

1.Refer to the above table and find the joint probability of the people who planned to purchase and actually placed an order.

2.Refer to the above table and find the joint probability of the people who planned to purchase and actually placed an order, given that people planned to purchase.

Question: 2

An electrical manufacturing company conducts quality checks at specified periods on the products it manufactures. Historically, the failure rate for the manufactured item is 5%. Suppose a random sample of 10 manufactured items is selected. Answer the following questions.

A. Probability that none of the items are defective?

B. Probability that exactly one of the items is defective?

C. Probability that two or fewer of the items are defective?

D. Probability that three or more of the items are defective ?

Question:3

A car salesman sells on an average 3 cars per week.

A. Probability that in a given week he will sell some cars.

B. Probability that in a given week he will sell 2 or more but less than 5 cars.

C. Plot the poisson distribution function for cumulative probability of cars sold per-week vs number of cars sold perweek.

Question: 4

Accuracy in understanding orders for a speech based bot at a restaurant is important for the Company X which has designed, marketed and launched the product for a contactless delivery due to the COVID-19 pandemic. Recognition accuracy that measures the percentage of orders that are taken correctly is 86.8%. Suppose that you place order with the bot and two friends of yours independently place orders with the same bot. Answer the following questions.

A. What is the probability that all three orders will be recognised correctly?

B. What is the probability that none of the three orders will be recognised correctly?

C. What is the probability that at least two of the three orders will be recognised correctly?

Question:5

A group of 300 professionals sat for a competitive exam. The results show the information of marks obtained by them have a mean of 60 and a standard deviation of 12. The pattern of marks follows a normal distribution. Answer the following questions.

A. What is the percentage of students who score more than 80.

B. What is the percentage of students who score less than 50.

C. What should be the distinction mark if the highest 10% of students are to be awarded distinction?

Question:6

Explain 1 real life industry scenario [other than the ones mentioned above] where you can use the concepts learnt in this module of Applied statistics to get a data driven business solution

There are some of the examples to explain the role of statistic in real life.

1) Medical Study

Statistics are used behind all the medical study. Statistic help doctors keep track of where the baby should be in his/her mental development. Physician’s also use statistics to examine the effectiveness of treatments.

2) Weather Forecasts

Statistics are very important for observation, analysis and mathematical prediction models. Weather forecast models are built using statistics that compare prior weather conditions with current weather to forecast future weather conditions.

3) Quality Testing

A company makes thousands of products every day and make sure that they sold the best quality items. For a company it is not possible to test each product. So the company uses quality test with the help of statistics.

4) Stock Market

The stock market also uses statistical computer models for stock analysis. Stock analysts get the information about economy using statistics concepts.

5) Consumer Goods

Retailers keeps track of everything they sell and to know the stock using statistics. Worldwide leading retailers use statistics to calculate what products ship to each store and when.

PART 2

PROJECT BASED

ATTRIBUTE INFORMATION:

  1. Team: Team’s name
  2. Tournament: Number of played tournaments.
  3. Score: Team’s score so far.
  4. PlayedGames: Games played by the team so far.
  5. WonGames: Games won by the team so far.
  6. DrawnGames: Games drawn by the team so far.
  7. LostGames: Games lost by the team so far.
  8. BasketScored: Basket scored by the team so far.
  9. BasketGiven: Basket scored against the team so far.
  10. TournamentChampion: How many times the team was a champion of the tournaments so far.
  11. Runner-up: How many times the team was a runners-up of the tournaments so far.
  12. TeamLaunch: Year the team was launched on professional basketball.
  13. HighestPositionHeld: Highest position held by the team amongst all the tournaments played.

There are 85.2% missing value in TournamentChampion & 78.7% in Runner-Up. So,drop that columns in the data set. Rest are small percentage of missing values. So, it can be filled with mean of the columns

Univariate Analysis

Multivariate analysis

Installing Pandas-Profiling

Use of Pandas Profiling

From the above details. Team 1 has highest performance

PART 3

PROJECT BASED

Description of the attribuites

  1. Startup: Name of the company
  2. Product: Actual product
  3. Funding: Funds raised by the company in USD
  4. Event: The event the company participated in
  5. Result: Described by Contestant, Finalist, Audience choice, Winner or Runner up
  6. OperatingState: Current status of the company, Operating ,Closed, Acquired or IPO

Statistical analysis:

First test,

Null hypothesis (Ho) : There is no difference between the two means

Alternate hypothesis (Ha) : There is significant difference between the two means

From the test above, There is no difference between the two means. Hence no evidance to state the companies that have raised more money tend to suceed more or vice-versa

Null hypothesis (Ho): The proportion of companies that are operating is the same in both categories - winners and contestants

Alternative hypothesis (Ha): The proportion of companies that are operating is significantly different from each other, among the two categories

Conclusion:

Null Hypothesis(Ho): Average funds raised by companies across three cities are the same

Alternative Hypothesis(Ha): Average funds raised by companies across three cities are the different

From the ANOVA test

---------------------------------------- THANK YOU -----------------------------------